Information intensive environments require observers of the information to make quick decisions in short time frames. An example of an information intensive environment is found in medicine in the surgical intensive care unit ("SICU"). In fact, a SICU is among the most information intensive environments in modern medicine. Monitors display vital functions of increasing sophistication but the displays are not uniform in design nor are they integrated, so that it is necessary for the clinician to survey several storage devices (including written records) at one time. Decisions in the SICU are often critical and urgent, and there is increasing pressure to reduce the time an individual is under intensive care and an increasing number of patients requiring such care. These conflicting considerations, that is, increased information and reduced time to assimilate it, create critical junctures in patient care in the SICU which may impair or delay the physician or other care giver from making accurate and safe judgments about the patient's immediate care. Current information visualization techniques are simply inadequate to facilitate the need for quick decisions.
Respiratory monitoring is a more specific example of the need in the SICU for fast and accurate decision making based on a great deal of critical information assaulting the physician in a short time. A few concepts are fundamental to respiratory care. Some, such as the three compartment model for gas exchange and the pressure/volume relationships for lung ventilation are approximately quantified in every patient as a conceptual basis for representing pathophysiology. Others such as the pulmonary vascular pressure/flow relationships or the effects of the distribution of ventilation/perfusion ratios are understood in theory but seldom quantitatively because they are technically difficult to measure or are approximate. Traditional and selected pulmonary measurements together with the volume-pressure model ("V/Q-P/Q Model") provide a means to estimate all these relationships and, for the first time, permit the interactions between the gas exchange and the blood flow properties of the lung in an individual patient to be assessed.
A large part of physician training is geared towards teaching physicians how to evaluate the changing variables presented by patients. This is achieved most often by development of mental representations of prototypical diseases and modified by experience, since it is well known that human beings can only accurately retain about seven items in short term memory. Such dependence on mental processing is inefficient and potentially inaccurate. There have been few attempts to display this complex data graphically and in such a form as to assist the clinician in the SICU or in other information intensive and demanding environments to process the data to derive quick decision-making abilities effectively.
Prior applications of computer-based information processing systems in medicine have been directed at pulmonary disease and particularly at respiratory intensive care. The earliest systems were directed at evaluating pulmonary function tests or providing smart alarms of malfunctions. Variations of these systems and improved data collection, display and calculation of some physiological variables have led to monitoring devices of the type that are now to be found in all intensive care units. Subsequent work has explored the use of computer based physician assistants, for example, to wean patients from mechanical ventilation, but the input required from the user was excessive.
Automatic data entry led to improved display of individual values and trends, but the applications were too narrow and research interest rapidly moved away from providing assistance to providing advice to physicians on diagnosis. However, even for the most sophisticated systems, the pathophysiology of cardiopulmonary function that they encompass is less advanced than that of an intensivist, and none of these systems has been adopted clinically. "Expert" systems have also been developed to inject artificial intelligence aspects into medical computer environments, but have generally been ineffective, since they cannot accurately make decisions in the place of physicians or clinicians.
Prior cognitive monitoring devices and methods therefore do not provide the physician or clinician with efficient and effective means for quickly analyzing data in an information-rich environment. There thus exists a long-felt but unfulfilled need in the monitoring art for methods and systems that will allow physicians or other clinicians to draw conclusions and make decisions as they are being bombarded by myriad forms of information in stressful environments such as the SICU.